The objective of this grant is to develop and implement new statistical methodology useful for genetic epidemiologic studies of complex chronic diseases such as cancer, coronary heart disease, allergy, as well as psychiatric illness. The focus will be on the development of statistical methods for: (I) analyzing multivariate survival data which occurs frequently when family data are collected to detect familial aggregation and to identify genetic subtypes of diseases with a late age-of-onset; (II) incorporating genetic heterogeneity and diagnostic ambiguity (or misdiagnosis) into the analysis of genetic linkage data; (III) addressing some statistical issues concerning the use of a relatively new method, the interval mapping method, to detect genetic linkage. For each of the specific aims, we will: (A) evaluate existing statistical methods and point out the place and the extent to which these methods may break down, (B) develop and study both analytically and empirically, new methods appropriate to the issues addressed above, (C) apply these methods to actual data sets of a variety of complex diseases which have motivated this proposed research. The work proposed here will both contribute statistical methodology to the field of genetic epidemiology in general, and offer insight into each of the clinical areas represented by the various data sets to illustrate these new methods.